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Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation


Jun 16, 2021
Haoxiang Wang, Han Zhao, Bo Li

* ICML 2021 camera-ready version. Code is released at https://github.com/AI-secure/multi-task-learning 

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Costs and Benefits of Wasserstein Fair Regression


Jun 16, 2021
Han Zhao


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Invariant Information Bottleneck for Domain Generalization


Jun 14, 2021
Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado J. Reed, Jun Zhang, Dongsheng Li, Kurt Keutzer, Han Zhao

* The work is in progress 

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Online Continual Adaptation with Active Self-Training


Jun 11, 2021
Shiji Zhou, Han Zhao, Shanghang Zhang, Lianzhe Wang, Heng Chang, Zhi Wang, Wenwu Zhu


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Quantifying and Improving Transferability in Domain Generalization


Jun 07, 2021
Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart

* 36 pages, 7 figures 

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Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations


Jun 05, 2021
Yao-Hung Hubert Tsai, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov


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Self-supervised Representation Learning with Relative Predictive Coding


Apr 12, 2021
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov


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Understanding and Mitigating Accuracy Disparity in Regression


Feb 24, 2021
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao


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Acoustic Structure Inverse Design and Optimization Using Deep Learning


Feb 18, 2021
Xuecong Sun, Han Jia, Yuzhen Yang, Han Zhao, Yafeng Bi, Zhaoyong Sun, Jun Yang


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Fundamental Limits and Tradeoffs in Invariant Representation Learning


Dec 19, 2020
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar


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Model-based Policy Optimization with Unsupervised Model Adaptation


Oct 28, 2020
Jian Shen, Han Zhao, Weinan Zhang, Yong Yu

* Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020) 

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Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation


Oct 12, 2020
Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Trevor Darrell, Kurt Keutzer, Han Zhao

* Preprint 

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Graph Adversarial Networks: Protecting Information against Adversarial Attacks


Oct 07, 2020
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoffrey Gordon, Stefanie Jegelka, Ruslan Salakhutdinov

* Our code is available at https://github.com/liaopeiyuan/GAL 

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DynamicVAE: Decoupling Reconstruction Error and Disentangled Representation Learning


Sep 30, 2020
Huajie Shao, Haohong Lin, Qinmin Yang, Shuochao Yao, Han Zhao, Tarek Abdelzaher


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A Review of Single-Source Deep Unsupervised Visual Domain Adaptation


Sep 19, 2020
Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer


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On Learning Language-Invariant Representations for Universal Machine Translation


Aug 11, 2020
Han Zhao, Junjie Hu, Andrej Risteski

* Appeared in ICML 2020 

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Neural Methods for Point-wise Dependency Estimation


Jun 11, 2020
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov


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Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift


Mar 10, 2020
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoff Gordon


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Continual Learning with Adaptive Weights (CLAW)


Nov 21, 2019
Tameem Adel, Han Zhao, Richard E. Turner


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Conditional Learning of Fair Representations


Oct 16, 2019
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon


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Learning Neural Networks with Adaptive Regularization


Jul 14, 2019
Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon


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Inherent Tradeoffs in Learning Fair Representation


Jun 19, 2019
Han Zhao, Geoffrey J. Gordon


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